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AEPsych uses GPs and active learning for adaptive experimentation, but there are older adaptive psychophysics methods, including the 1-up-N-down staircase (https://en.wikipedia.org/wiki/Psychophysics#Staircase_procedures). This method is still useful for finding thresholds along single dimensions. The algorithm has 3 parameters: N, step-up size, and step-down size. After the participant makes the correct response N times, the stimulus parameter is increased by step-up size. If they make an incorrect response, the parameter is reduced by step-down size. This algorithm can be implemented using an AEPsyh generator class. All parameters should be configurable via .ini files.
The text was updated successfully, but these errors were encountered:
AEPsych uses GPs and active learning for adaptive experimentation, but there are older adaptive psychophysics methods, including the 1-up-N-down staircase (https://en.wikipedia.org/wiki/Psychophysics#Staircase_procedures). This method is still useful for finding thresholds along single dimensions. The algorithm has 3 parameters: N, step-up size, and step-down size. After the participant makes the correct response N times, the stimulus parameter is increased by step-up size. If they make an incorrect response, the parameter is reduced by step-down size. This algorithm can be implemented using an AEPsyh generator class. All parameters should be configurable via .ini files.
The text was updated successfully, but these errors were encountered: